Factors affecting apparent prevalence of tuberculosis and brucellosis in wood bison
Bibliographic record
Abstract
Summary Bison (Bison bison) abundance in Wood Buffalo National Park, Canada, declined from in excess of 10 000 bison in the late 1960s to a low of 2200 bison in the late 1990s. Bovine tuberculosis (Mycobacterium bovis) and brucellosis (Brucella abortus), were introduced to Wood Buffalo National Park in the late 1920s. As each of these pathogens have the potential to reduce survival and reproduction in bison, they are suspected to have played a role in the decline in bison abundance. We live‐captured bison for disease testing in February and March of 1997, 1998 and 1999. Forty‐nine percent tested positive for tuberculosis (i.e. were positive on the caudal fold test and/or fluorescent polarization assay,n = 342). Further, 30·9% of bison were seropositive for brucellosis (i.e. agglutinated in the buffered‐plate antigen test and had a titre of 1 : 5 in the complement fixation test or had a titre of ≥ 1 : 10 in the complement fixation test,n = 346). Prevalence for both diseases increased with age and males were more likely to test positive for tuberculosis. Prevalence of either disease did not appear to be directly related to density of bison, as prevalence rates were not greater in the high density Delta population than the lower density Hay Camp and Nyarling River populations. Comparison of our results to previous brucellosis and tuberculosis surveys in Wood Buffalo National Park indicates that prevalence of neither pathogen is a direct function of bison density. These pathogens are endemic within the bison population of the park.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".